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融合事故表征和CBR的特种设备事故预测方法及结果比较OA

Special Equipment Accident Prediction Methods Integrating Accident Characterization and CBR and Result Comparison

中文摘要英文摘要

特种设备是指涉及生命安全、危险性较高的锅炉、压力容器、电梯、起重机械等设备,常用于工业生产与居民日常活动中.针对特种设备事故预测难度大、精细度低、成本高等问题,为进一步提高特种设备故障预测精度,提出了一种融合事故表征和案例推理(Case-based Reasoning,CBR)的特种设备事故预测方法.在研究过程中,首先通过分析特种设备事故原因与构建事故表征结构模型,梳理特种设备事故表征.再通过明确事故表征规范与事故表征信息编码,构建形成事故表征案例库.最后通过进行属性权重计算、案例相似度计算以及事故发生概率预测,总结出融合事故表征和CBR的特种设备事故预测方法,以提高特种设备预测结果精准度,打破目前仅用事故表征法预测特种设备事故的局限,保障特种设备的安全运行.

Special equipment refers to boilers,pressure vessels,elevators,lifting machinery,and other equipment that involve life safety and high risk.It is commonly used in industrial production and daily activities of residents.In response to the problems of high difficulty,low precision,and high cost in predicting special equipment accidents,in order to further improve the accuracy of special equipment fault prediction,a special equipment accident prediction method integrating accident characterization and case based reasoning(CBR)is proposed.In the research process,firstly,by analyzing the causes of special equipment accidents and constructing a structural model for accident characterization,the characterization of special equipment accidents is sorted out.By clarifying accident characterization standards and encoding accident characterization information,a case library of accident characterization is constructed.Finally,by performing attribute weight calculation,case similarity calculation,and accident probability prediction,a special equipment accident prediction method that integrates accident characterization and CBR is summarized to improve the accuracy of special equipment prediction results,break the limitation of only using accident table theory to predict special equipment accidents,and ensure the safe operation of special equipment.

孙浩翔;季一锦

江苏省特种设备安全监督检验研究院,南京 210036

计算机与自动化

事故表征特种设备故障表征信息案例推理

accident characterizationspecial equipmentfault characterization informationcase-based reasoning

《机电工程技术》 2024 (005)

214-217 / 4

10.3969/j.issn.1009-9492.2024.05.047

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